Real-time symptom monitoring using ePROs to prevent adverse events during care transitions

使用 ePRO 进行实时症状监测，以预防护理过渡期间的不良事件

• 批准号: 10345512
• 负责人: Anuj K Dalal
• 金额: $ 40万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10345512
• 关键词: Real; time; symptom; monitoring; using

ABSTRACT Adverse events (AE) during care transitions range from 19-28% and may lead to readmissions, representing an ongoing threat to patient safety. Early identification and escalation of patient-reported symptoms to inpatient and ambulatory clinicians is critical, especially for patients with multiple chronic conditions (MCC). Clinically integrated digital health apps have the potential to more accurately predict post-discharge AEs and improve communication for patients, their caregivers, and the care team. Such tools can provide individualized risk assessments of AEs by systematically collecting relevant patient-reported outcomes (PROs) and leveraging standardized application programming interfaces (API) to combine them with electronic health record (EHR) data. While patient-reported outcomes (PROs) are increasingly used in ambulatory settings, their use for real- time symptom monitoring and escalation during transitions from the hospital is novel and potentially transformative–by both empowering patients to better understand their individualized risks of post-discharge AEs, and improving monitoring while transitioning out of the hospital. Our proposed intervention is grounded in evidence-based frameworks for care transitions, and scaling and spread of digital health tools. To inform our intervention, we propose developing and validating a predictive model of post-discharge AEs for hospitalized MCC patients using relevant PRO questionnaires and electronic health record (EHR) derived variables. We will then combine, adapt, extend, and refine our previously developed EHR-integrated hospital and ambulatory-focused digital health infrastructure to support MCC patients in real-time symptom monitoring using PROs when transitioning out of the hospital. Our intervention uses interoperable, data exchange standards and APIs to seamlessly integrate with existing vendor patient portal offerings, thereby addressing critical gaps and supporting the complete continuum of care. Our multidisciplinary team uses principles of user-centered design and agile software development to rapidly identify, design, develop, refine, and implement requirements from patients and clinicians. Our team will rigorously evaluate this intervention in a large-scale randomized controlled trial in which we compare our real-time symptom monitoring intervention to usual care for patients with MCCs transitioning out of the hospital. Finally, we will conduct a robust mixed methods evaluation to generate new knowledge and best practices for disseminating, implementing, and using this interoperable intervention at similar institutions with different EHR vendors.

抽象的 护理过渡期间的不良事件（AE）范围为19-28％，可能导致再入院 对患者安全的持续威胁。 卧床临床医生至关重要，特别是对于具有多种慢性病（MCC）的患者。 集成的数字健康应用程序有可能更多地预测放电后AES并改善 患者，护理人员和护理团队的沟通可以提供个人风险 通过系统地收集相关患者报告的结果（专业）和利用来评估AES 标准化应用程序界面（API）将它们与电子健康记录（EHR）相结合 数据。 从医院过渡期间的时间症状监测和升级是新颖且具有稳定的 通过赋予患者能够更好地了解个性化的释放风险 AES，并在过渡出医院时改善监测。 基于证据的护理过渡的循证框架，数字健康的扩展和扩散。 干预，我们建议开发和验证以及住院后AES的预测模型 MCC患者使用Revant Pro问卷和电子健康记录（EHR）衍生的变量 然后将组合，适应，扩展和完善我们先前开发的EHR集成的Hosspital和 以实时症状监测的MCC患者支持MCC患者，以卧床为中心的数字健康基础结构 从医院过渡时使用专业人士。 标准和API与现有的供应商患者门户产品无缝集成，从而解决 关键的差距并支持我们的多学科团队 以用户为中心的设计和敏捷软件软件开发，以迅速识别，设计，开发，完善，Andine 我们团队的患者和临床医生的要求将严格评估 大规模随机对照试验，我将实时症状监测干预与 对于MCC患者过渡的患者通常会护理。 方法评估以产生新知识和最佳实践，以传播，实施和 在类似研究所使用这种可互操作的干扰与不同的EHR供应商。